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# Model description
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This is a multivector retrieval model that is built upon the efficient [XTR](https://proceedings.neurips.cc/paper_files/paper/2023/hash/31d997278ee9069d6721bc194174bb4c-Abstract-Conference.html) architecture. The model utilizes [t5-base](https://huggingface.co/t5-base) encoder, and is finetuned on [MSMarco](https://huggingface.co/datasets/BeIR/msmarco) dataset
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# Overview
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*Data*: MSMarco
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# Intented use
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This model can be utilized for text retrieval (IR). You can find detailed instructions and examples on how to use this model for text retrieval in the [
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# Model description
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This is a multivector retrieval model that is built upon the efficient [XTR](https://proceedings.neurips.cc/paper_files/paper/2023/hash/31d997278ee9069d6721bc194174bb4c-Abstract-Conference.html) architecture. The model utilizes [t5-base](https://huggingface.co/t5-base) encoder, and is finetuned on [MSMarco](https://huggingface.co/datasets/BeIR/msmarco) dataset with XTR objective.
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# Overview
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*Data*: MSMarco
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# Intented use
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This model can be utilized for text retrieval (IR). You can find detailed instructions and examples on how to use this model for text retrieval in the documentation [here](https://github.com/primeqa/primeqa/blob/xtr/notebooks/ir/dense/xtr_retrieval.ipynb).
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